#####################################################################
import os
BETA_INIT = 1e-4
BETA_FINAL = 0.02
BATCH_SIZE = 64
DEVICE = 'cuda'
T = 1000  # total steps.
LEARNING_RATE = 1e-4
weight_decay = 1e-4
warm_up_steps = 5
grad_clip = 1
EPOCHS = 20
SAVE_ON_EPOCH = 2
SAMPLE_ON_EPOCH = 1
####################### model ralated #######################
CHANNEL_BASELINE = 32
HEAD_CONV_OUT_CHANNELS = 128
CONVNEXT_CHANNEL_OUT_FACTOR = 2
RESNET_BLOCK_GROUPS = 8
_CHECKPOINT_SAVE_PATH = os.path.split(os.path.realpath(__file__))[0] + "\\checkpoint\\"
MODEL_SAVE_PATH = _CHECKPOINT_SAVE_PATH + 'model.pt'
OPTIMIZER_SAVE_PATH = _CHECKPOINT_SAVE_PATH + 'optimizer.pt'
####################### image ralated #######################
C = 1
H = 64
W = 64
TENSOR_SHAPE = [BATCH_SIZE,C,H,W]
IMAGE_SIZE = 512

TRAINING_DATASET = "X:\Machine_Learning\datasets\AnimeFaces\subset\\faces"

